Dataset for floating objects detection
Perhaps you can check this dataset out:
http://www.aiskyeye.com/


  The VisDrone2019 dataset is collected by the AISKYEYE team at Lab of
  Machine Learning and Data Mining , Tianjin University, China. The
  benchmark dataset consists of 288 video clips formed by 261,908 frames
  and 10,209 static images, captured by various drone-mounted cameras,
  covering a wide range of aspects including location (taken from 14
  different cities separated by thousands of kilometers in China),
  environment (urban and country), objects (pedestrian, vehicles,
  bicycles, etc.), and density (sparse and crowded scenes). Note that,
  the dataset was collected using various drone platforms (i.e., drones
  with different models), in different scenarios, and under various
  weather and lighting conditions. These frames are manually annotated
  with more than 2.6 million bounding boxes of targets of frequent
  interests, such as pedestrians, cars, bicycles, and tricycles. Some
  important attributes including scene visibility, object class and
  occlusion, are also provided for better data utilization.


It provides many drone view images with bounding boxes. Hope it can help you and have a nice day!